A fuzzy multi-criteria decision framework for community isolation center site selection to enhance public health resilience

Infectious disease outbreaks require effective emergency preparedness strategies, including the rapid deployment of community isolation centers. However, selecting suitable locations for these facilities is a complex decision-making problem involving multiple criteria and significant uncertainty, especially regarding public acceptance and infrastructure readiness. This research proposes a fuzzy multi-criteria decision-making framework to support location selection that enhances both operational efficiency and community resilience. The framework defines community resilience not only as the ability to recover from health shocks but also as the capacity to engage with, support, and accept local public health interventions. The model integrates the fuzzy analytic hierarchy process and the fuzzy technique for order preference by similarity to the ideal solution using trapezoidal fuzzy numbers to better represent uncertainty in expert judgments and ambiguity in community feedback. A real-world case study from Chiang Mai, Thailand, evaluates six candidate sites based on criteria such as accessibility, environmental impact, community consent, and emergency readiness. The results demonstrate the model’s capacity to support context-sensitive, transparent, and resilient public health decision-making. This approach contributes to safety science by offering a reproducible and computationally efficient decision-support tool that improves the siting of health infrastructure in response to pandemics. It emphasizes the integration of technical and social dimensions to support emergency preparedness and long-term resilience in vulnerable communities.